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Through a reflective analysis grounded in existing literature, including case studies and theoretical frameworks from software engineering and AI ethics, we examine the specific manifestations of bias in code generation, focusing on how training data contribute to these issues. We investigate the challenges associated with interpreting LLM-generated code, highlighting the lack of transparency and the potential for hidden biases, and explore the security risks introduced by biased LLMs, namely vulnerabilities that may be exploited by malicious actors. We provide several recommendations for mitigating these challenges, emphasizing the need to refine training data and involve humans-in-the-loop.<\/jats:p>","DOI":"10.1145\/3774324","type":"journal-article","created":{"date-parts":[[2025,10,31]],"date-time":"2025-10-31T06:19:11Z","timestamp":1761891551000},"page":"1-16","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["SE Perspective on LLMs: Biases in Code Generation, Code Interpretability, and Code Security Risks"],"prefix":"10.1145","volume":"58","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6884-6131","authenticated-orcid":false,"given":"Rrezarta","family":"Krasniqi","sequence":"first","affiliation":[{"name":"Department of Software and Information Systems, The University of North Carolina at Charlotte","place":["Charlotte, United States"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0371-1815","authenticated-orcid":false,"given":"Depeng","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Software and Information Systems, The University of North Carolina at Charlotte","place":["Charlotte, United States"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5103-8541","authenticated-orcid":false,"given":"Marco","family":"Vieira","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of North Carolina at Charlotte","place":["Charlotte, United States"]}]}],"member":"320","published-online":{"date-parts":[[2025,12,4]]},"reference":[{"key":"e_1_3_1_2_2","unstructured":"Wayne Xin Zhao Kun Zhou Junyi Li Tianyi Tang Xiaolei Wang Yupeng Hou Yingqian Min Beichen Zhang Junjie Zhang Zican Dong et\u00a0al. 2023. 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